1. Field of the Invention
This invention relates to wireless communications—in particular to diversity combining in a receiver employing an antenna array in order to achieve adaptive directional reception, exploit multi-path signal reception, suppress co-channel interference and allow space division multiplexing.
2. Brief Description of Related Art
In the area of burst wireless communications the directional signal transmission and reception enhance all the performance metrics of the communication links such as range, throughput rate, emitted signal power, power dissipation, as well as link reliability and interference immunity. Directionality is achieved by employing an antenna array controlled by a beamformer logic at the transmitter site and a signal combiner logic at the receiver site. Antenna arrays can also be coupled with logic for supporting multiple communication links with spatially separated users that share the same spectrum and time frame. For example, spatial division multiple access (SDMA) systems are based on this notion. The above pieces of logic can be modeled in many different ways [1].
However, incorporating high performance adaptation techniques in practical applications is a highly non-trivial task because of the computational complexity factor.
A number of different methods for diversity combining and co-channel interference suppression for wireless burst communications systems have been proposed. However, these methods suffer from one or more weaknesses such as the need of unrealistic modeling assumptions, high computational complexity, slow convergence and the need of coupling with ad-hoc algorithms that alleviate the above.
For example, in [2] the noise power and instant subcarrier energy estimations are used for computing a diversity combiner weight vector in OFDM signaling. In particular, with reference to FIG. 1, a flowchart of operation of this prior art diversity combiner 10 begins with power up block 11. When a symbol 12 is received, the noise power is estimated in block 13 based on some unloaded carriers. For every loaded subcarrier in the said symbol a sequence of five tasks 14 takes place. The subcarrier is received in block 15, its instant energy gets estimated in block 16 and subsequently accumulated to update the subcarrier energy estimation in block 17. Next, the diversity combiner weight vector respective to the said subcarrier gets computed in block 18 on the basis of the subcarrier instant energy, the subcarrier energy estimation and the said noise power. Finally the weight vector is applied in block 19 to the diversity combiner and the data logic level is extracted. The performance of this method depends on the quality of the noise power estimator and consequently the number and structure of the unloaded carriers. In addition, the weights are estimated on the basis of energy measurements only, so the expected quality of performance is poor and therefore an ad-hoc co-phasing algorithm needs to be coupled within the method. Furthermore, this method cannot be used for interference cancellation.
In [3] and [4], two categories of algorithms for diversity combining and co-channel interference suppression are reviewed. In the first category, the direction of arrival (DOA) of the beam needs to be identified at the receiver. This presents many deficiencies. First, DOA estimation is an extremely computation intensive process that cannot be implemented efficiently in the current art of semiconductor technology, thus it cannot find applications in high volume consumer products. Second, the DOA estimation methods are very sensitive to model imperfections such as antenna element intervals and antenna array geometry. Third, the number of antenna elements in the antenna array limits the number of multipaths and interferers DOA based methods can cope with.
In the second category, a training sequence is required along with an estimation of the correlation with this training sequence and the input signal correlations. Although the problems of the algorithms in the previous paragraph are avoided, the need for estimating the correlations of the input signals introduces a slow convergence rate algorithm especially in relation to multicarrier wireless communication systems. For instance, averaging over a particular subcarrier requires multiple multicarrier symbols.